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Evaluating the suitability of multi-scale terrain attribute calculation approaches for seabed mapping applications / Benjamin Misiuk in Marine geodesy, vol 44 n° 4 (July 2021)
[article]
Titre : Evaluating the suitability of multi-scale terrain attribute calculation approaches for seabed mapping applications Type de document : Article/Communication Auteurs : Benjamin Misiuk, Auteur ; Vincent Lecours, Auteur ; M.F.J. Dolan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 327 - 385 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] analyse multiéchelle
[Termes IGN] artefact
[Termes IGN] attribut géomètrique
[Termes IGN] carte bathymétrique
[Termes IGN] cartographie hydrographique
[Termes IGN] fond marin
[Termes IGN] géomorphométrie
[Termes IGN] habitat animal
[Termes IGN] pente
[Termes IGN] réalité de terrain
[Termes IGN] rugosité
[Termes IGN] sondeur multifaisceaux
[Termes IGN] Terre-Neuve, île de (Terre-Neuve-et-Labrador)Résumé : (auteur) The scale dependence of benthic terrain attributes is well-accepted, and multi-scale methods are increasingly applied for benthic habitat mapping. There are, however, multiple ways to calculate terrain attributes at multiple scales, and the suitability of these approaches depends on the purpose of the analysis and data characteristics. There are currently few guidelines establishing the appropriateness of multi-scale raster calculation approaches for specific benthic habitat mapping applications. First, we identify three common purposes for calculating terrain attributes at multiple scales for benthic habitat mapping: (i) characterizing scale-specific terrain features, (ii) reducing data artefacts and errors, and (iii) reducing the mischaracterization of ground-truth data due to inaccurate sample positioning. We then define criteria that calculation approaches should fulfill to address these purposes. At two study sites, five raster terrain attributes, including measures of orientation, relative position, terrain variability, slope, and rugosity were calculated at multiple scales using four approaches to compare the suitability of the approaches for these three purposes. Results suggested that specific calculation approaches were better suited to certain tasks. A transferable parameter, termed the ‘analysis distance’, was necessary to compare attributes calculated using different approaches, and we emphasize the utility of such a parameter for facilitating the generalized comparison of terrain attributes across methods, sites, and scales. Numéro de notice : A2021-526 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/01490419.2021.1925789 Date de publication en ligne : 04/06/2021 En ligne : https://doi.org/10.1080/01490419.2021.1925789 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97967
in Marine geodesy > vol 44 n° 4 (July 2021) . - pp 327 - 385[article]Fluvial gravel bar mapping with spectral signal mixture analysis / Liza Stančič in European journal of remote sensing, vol 54 sup 1 (2021)
[article]
Titre : Fluvial gravel bar mapping with spectral signal mixture analysis Type de document : Article/Communication Auteurs : Liza Stančič, Auteur ; Krištof Oštir, Auteur ; Žiga Kokalj, Auteur Année de publication : 2021 Article en page(s) : pp 31 - 46 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] bassin hydrographique
[Termes IGN] carte thématique
[Termes IGN] gravier
[Termes IGN] image Landsat
[Termes IGN] image Sentinel-MSI
[Termes IGN] précision infrapixellaire
[Termes IGN] réflectance spectrale
[Termes IGN] rivière
[Termes IGN] signature spectrale
[Termes IGN] SlovénieRésumé : (auteur) The paper presents a method for mapping fluvial gravel bars based on Sentinel-2 and Landsat imagery. The proposed method therefore uses spectral signal mixture analysis (SSMA) because its results allow the development of land cover fraction maps for surface water, gravel, and vegetation. The method is validated on a spatially heterogeneous mountainous area in the upper Soča river basin in north-west Slovenia, Central Europe. Unmixing results in highly accurate fraction maps with MAE of around 0.1. Gravel fractions are mapped the most accurately, indicating that the approach can be used successfully for fluvial gravel bar mapping. Endmember sets selected automatically perform slightly worse (MAE higher by at most 0.05) than sets selected manually based on high resolution reference data. Both Sentinel-2 and Landsat imagery can be used for accurate mapping with differences between the two remote sensing systems within 0.05 MAE. For the study area, the SSMA-based soft classification method is more accurate for land cover mapping than a Spectral Angle Mapping-based hard classification. The method is promising for an effective use in other cases where highly accurate subpixel information is needed, because it is able to detect small-scale changes that could go unnoticed with hard classification mapping. Numéro de notice : A2021-817 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2020.1811776 Date de publication en ligne : 30/08/2020 En ligne : https://doi.org/10.1080/22797254.2020.1811776 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98906
in European journal of remote sensing > vol 54 sup 1 (2021) . - pp 31 - 46[article]GIS in soil survey and soil mapping / Perparim Ameti in Geodesy and cartography, vol 47 n° 2 (July 2021)
[article]
Titre : GIS in soil survey and soil mapping Type de document : Article/Communication Auteurs : Perparim Ameti, Auteur ; Besim Ajvasi, Auteur Année de publication : 2021 Article en page(s) : pp 80 - 88 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] carte pédologique
[Termes IGN] géodatabase
[Termes IGN] Kosovo
[Termes IGN] lever mobile
[Termes IGN] planification
[Termes IGN] qualité du sol
[Termes IGN] SIG nomade
[Termes IGN] système d'information géographique
[Termes IGN] utilisation du solRésumé : (auteur) The main goal of this paper is to present a methodology for land evaluation by supporting decision-makers with reliable information for the land-use planning process. One of the focuses of this paper is given to the survey process and interpretation between soil survey, soil survey interpretation, and physical land evaluation. Such processes are realized using mobile mapping tools with integrated Global Position Systems (GPS) and Geographic Information Systems (GIS). Both have increased the efficiency of data communication technologies by enabling real-time communication between people located in the field and office as well. For the soil classification as a key component of soil surveys is used World Reference Base (WRB) for Soil Resources. This is a common tool to summarize the wealth of information from soil profiles for the purpose of land evaluation. The final results showed a soil classification map. Such results are derived from many activities, since it includes a preliminary land evaluation, field soil survey with auger holes and profiles as well. This methodology is used for the first time in the selected study area. Numéro de notice : A2021-567 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3846/gac.2021.12116 Date de publication en ligne : 15/07/2021 En ligne : https://doi.org/10.3846/gac.2021.12116 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98137
in Geodesy and cartography > vol 47 n° 2 (July 2021) . - pp 80 - 88[article]Road-network-based fast geolocalization / Yongfei Li in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)
[article]
Titre : Road-network-based fast geolocalization Type de document : Article/Communication Auteurs : Yongfei Li, Auteur ; Dongfang Yang, Auteur ; Shisheng Wang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 6065 - 6076 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carrefour
[Termes IGN] carte routière
[Termes IGN] cohérence géométrique
[Termes IGN] géolocalisation
[Termes IGN] image aérienne
[Termes IGN] réseau routier
[Termes IGN] segmentation d'image
[Termes IGN] semis de points
[Termes IGN] superposition d'images
[Termes IGN] transformation homographique
[Termes IGN] zone urbaineRésumé : (auteur) In this article, a road-network-based geolocalization method is proposed. We match roads in the onboard images to the reference road vector map, and realize successful localization over areas as large as a whole city. The road network matching problem is treated as a point cloud registration problem under the homography transformation and solved under the hypothesize-and-test framework. To tackle the point cloud registration problem, a global projective-invariant feature is proposed, which consists of two road intersections augmented with their tangents. In addition, we propose the necessary conditions for the features to match. This can reduce the candidate matching features, thus accelerating the search to a great extent. These matching candidates are first “filtered” with the model consistency check in parameter space and then tested with similarity metrics to identify the correct transformation. The experiments show that our method can localize an aerial image over an area larger than 1000 km 2 within several seconds on a single CPU. Our code can be found at: https://github.com/FlyAlCode/RCLGeolocalization-2.0 . Numéro de notice : A2021-532 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3011034 Date de publication en ligne : 18/08/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3011034 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97989
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 7 (July 2021) . - pp 6065 - 6076[article]Forest cover mapping and Pinus species classification using very high-resolution satellite images and random forest / Laura Alonso-Martinez in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)
[article]
Titre : Forest cover mapping and Pinus species classification using very high-resolution satellite images and random forest Type de document : Article/Communication Auteurs : Laura Alonso-Martinez, Auteur ; J. Picos, Auteur ; Julia Armesto, Auteur Année de publication : 2021 Article en page(s) : pp 203 - 210 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] carte de la végétation
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] couvert forestier
[Termes IGN] Espagne
[Termes IGN] Eucalyptus (genre)
[Termes IGN] image multibande
[Termes IGN] image Worldview
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Pinus pinaster
[Termes IGN] Pinus radiata
[Termes IGN] Pinus sylvestris
[Termes IGN] ressources forestières
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Advances in remote sensing technologies are generating new perspectives concerning the role of and methods used for National Forestry Inventories (NFIs). The increase in computation capabilities over the last several decades and the development of new statistical techniques have allowed for the automation of forest resource map generation through image analysis techniques and machine learning algorithms. The availability of large-scale data and the high temporal resolution that satellite platforms provide mean that it is possible to obtain updated information about forest resources at the stand level, thus increasing the quality of the spatial information. However, photointerpretation of satellite and aerial images is still the most common way that remote sensing information is used for NFIs or forest management purposes. This study describes a methodology that automatically maps the main forest covers in Galicia (Eucalyptus spp., conifers and broadleaves) using Worldview-2 and the random forest classifier. Furthermore, the method also evaluates the separate mapping of the three most abundant Pinus tree species in Galicia (Pinus pinaster, Pinus radiata and Pinus sylvestris). According to the results, Worldview-2 multispectral images allow for the efficient differentiation between the main forest classes that are present in Galicia with a very high degree of accuracy (91%) and ample spatial detail. Pinus species can also be efficiently differentiated (83%). Numéro de notice : A2021-493 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.5194/isprs-annals-V-3-2021-203-2021 Date de publication en ligne : 17/06/2021 En ligne : http://dx.doi.org/10.5194/isprs-annals-V-3-2021-203-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97958
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2021 (July 2021) . - pp 203 - 210[article]Coral habitat mapping: a comparison between maximum likelihood, Bayesian and Dempster–Shafer classifiers / Mohammad Shawkat Hossain in Geocarto international, vol 36 n° 11 ([15/06/2021])PermalinkGroundwater vulnerability assessment of the chalk aquifer in the northern part of France / Lahcen Zouhri in Geocarto international, vol 36 n° 11 ([15/06/2021])PermalinkMapping fine-scale human disturbances in a working landscape with Landsat time series on Google Earth Engine / Tongxi Hu in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)PermalinkProvisioning forest and conservation science with high-resolution maps of potential distribution of major European tree species under climate change / Debojyoti Chakraborty in Annals of Forest Science, vol 78 n° 2 (June 2021)PermalinkResolution enhancement for large-scale land cover mapping via weakly supervised deep learning / Qiutong Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 6 (June 2021)PermalinkWalking through the forests of the future: using data-driven virtual reality to visualize forests under climate change / Jiawei Huang in International journal of geographical information science IJGIS, vol 35 n° 6 (June 2021)PermalinkElectrical resistivity, remote sensing and geographic information system approach for mapping groundwater potential zones in coastal aquifers of Gurpur watershed / H.S. Virupaksha in Geocarto international, vol 36 n° 8 ([01/05/2021])PermalinkEvaluation of light pollution in global protected areas from 1992 to 2018 / Haowei Mu in Remote sensing, vol 13 n° 9 (May-1 2021)PermalinkWhat is the difference between augmented reality and 2D navigation electronic maps in pedestrian wayfinding? / Weihua Dong in Cartography and Geographic Information Science, vol 48 n° 3 (May 2021)PermalinkDecision-level and feature-level integration of remote sensing and geospatial big data for urban land use mapping / Jiadi Yin in Remote sensing, vol 13 n° 8 (April-2 2021)Permalink